• Title/Summary/Keyword: Inertial Sensor Module System

Search Result 14, Processing Time 0.023 seconds

Single Gyroscope Sensor Module System for Gait Event Detection (보행시점 검출을 위한 단일 각속도 센서모듈 시스템)

  • Kang, Dong-Won;Choi, Jin-Seung;Kim, Han-Su;Oh, Ho-Sang;Seo, Jeong-Woo;Tack, Gye-Rae
    • Korean Journal of Applied Biomechanics
    • /
    • v.21 no.4
    • /
    • pp.495-501
    • /
    • 2011
  • The purpose of this study was to develop the inertial sensor module system to detect gait event using single angular rate sensor(gyroscope), and evaluate the accuracy of this system. This sensor module is attached at the heel and gait events such as heel strike, foot flat, heel off, toe off are detected by using proposed automatic event detection algorithm. The developed algorithm detect characteristics of pitch data of the gyroscope to find gait event. To evaluate the accuracy of system, 3D motion capture system was used and synchronized with sensor module system for comparison of gait event timings. In experiment, 6 subjects performed 5 trials level walking with 3 different conditions such as slow, preferred and fast. Results showed that gait event timings by sensor module system are similar to that by kinematic data, because maximum absolute errors were under 37.4msec regardless of gait velocity. Therefore, this system can be used to detect gait events. Although this system has advantages of small, light weight, long-term monitoring and high accuracy, it is necessary to improve the system to get other gait information such as gait velocity, stride length, step width and joint angles.

Hybrid Inertial and Vision-Based Tracking for VR applications (가상 현실 어플리케이션을 위한 관성과 시각기반 하이브리드 트래킹)

  • Gu, Jae-Pil;An, Sang-Cheol;Kim, Hyeong-Gon;Kim, Ik-Jae;Gu, Yeol-Hoe
    • Proceedings of the KIEE Conference
    • /
    • 2003.11b
    • /
    • pp.103-106
    • /
    • 2003
  • In this paper, we present a hybrid inertial and vision-based tracking system for VR applications. One of the most important aspects of VR (Virtual Reality) is providing a correspondence between the physical and virtual world. As a result, accurate and real-time tracking of an object's position and orientation is a prerequisite for many applications in the Virtual Environments. Pure vision-based tracking has low jitter and high accuracy but cannot guarantee real-time pose recovery under all circumstances. Pure inertial tracking has high update rates and full 6DOF recovery but lacks long-term stability due to sensor noise. In order to overcome the individual drawbacks and to build better tracking system, we introduce the fusion of vision-based and inertial tracking. Sensor fusion makes the proposal tracking system robust, fast, accurate, and low jitter and noise. Hybrid tracking is implemented with Kalman Filter that operates in a predictor-corrector manner. Combining bluetooth serial communication module gives the system a full mobility and makes the system affordable, lightweight energy-efficient. and practical. Full 6DOF recovery and the full mobility of proposal system enable the user to interact with mobile device like PDA and provide the user with natural interface.

  • PDF

Design and estimation of a sensing attitude algorithm for AUV self-rescue system

  • Yang, Yi-Ting;Shen, Sheng-Chih
    • Ocean Systems Engineering
    • /
    • v.7 no.2
    • /
    • pp.157-177
    • /
    • 2017
  • This research is based on the concept of safety airbag to design a self-rescue system for the autonomous underwater vehicle (AUV) using micro inertial sensing module. To reduce the possibility of losing the underwater vehicle and the difficulty of searching and rescuing, when the AUV self-rescue system (ASRS) detects that the AUV is crashing or encountering a serious collision, it can pump carbon dioxide into the airbag immediately to make the vehicle surface. ASRS consists of 10-DOF sensing module, sensing attitude algorithm and air-pumping mechanism. The attitude sensing modules are a nine-axis micro-inertial sensor and a barometer. The sensing attitude algorithm is designed to estimate failure attitude of AUV properly using sensor calibration and extended Kalman filter (SCEKF), feature extraction and backpropagation network (BPN) classify. SCEKF is proposed to be used subsequently to calibrate and fuse the data from the micro-inertial sensors. Feature extraction and BPN training algorithms for classification are used to determine the activity malfunction of AUV. When the accident of AUV occurred, the ASRS will immediately be initiated; the airbag is soon filled, and the AUV will surface due to the buoyancy. In the future, ASRS will be developed successfully to solve the problems such as the high losing rate and the high difficulty of the rescuing mission of AUV.

A Study on the HWIL Simulation System of the Flight Object including Inertial Navigation System (관성항법장치가 포함된 비행체의 HWIL 시뮬레이션 시스템 개발 연구)

  • Lee, Ayeong
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.21 no.3
    • /
    • pp.349-360
    • /
    • 2018
  • This paper proposes various methods for constructing a HWIL simulation system including Inertial Navigation System(INS) and Guidance Control Unit(GCU) under the assumption that the INS identifies the initial attitude of an aviation body through its own alignment and that it is a package consisting of an inertial sensor and a navigation computation module. This paper also presents a real-time computing technology and a way to calculate the command of the Flight Motion System(FMS) analogous to the acutal flight environment. The proposed HWIL simulation system is constructed by applying the above-mentioned methods and the results of running a series of simulations confirm high effectiveness and usefulness of the system. Finally, minor error factors that could be acquired only in HWIL simulation Environment are analyzed.

Paddling Posture Correction System Using IMU Sensors

  • Kim, Kyungjin;Park, Chan Won
    • Journal of Sensor Science and Technology
    • /
    • v.27 no.2
    • /
    • pp.86-92
    • /
    • 2018
  • In recent times, motion capture technology using inertial measurement unit (IMU) sensors has been actively used in sports. In this study, we developed a canoe paddle, installed with an IMU and a water level sensor, as a system tool for training and calibration purposes in water sports. The hardware was fabricated to control an attitude heading reference system (AHRS) module, a water level sensor, a communication module, and a wireless charging circuit. We also developed an application program for the mobile device that processes paddling motion data from the paddling operation and also visualizes it. An AHRS module with acceleration, gyro, and geomagnetic sensors each having three axes, and a resistive water level sensor that senses the immersion depth in the water of the paddle represented the paddle motion. The motion data transmitted from the paddle device is internally decoded and classified by the application program in the mobile device to perform visualization and to operate functions of the mobile training/correction system. To conclude, we tried to provide mobile knowledge service through paddle sport data using this technique. The developed system works reasonably well to be used as a basic training and posture correction tool for paddle sports; the transmission delay time of the sensor system is measured within 90 ms, and it shows that there is no complication in its practical usage.

Implementation of Motion Analysis System based on Inertial Measurement Units for Rehabilitation Purposes (재활훈련을 위한 관성센서 기반 동작 분석 시스템 구현)

  • Kang, S.I.;Cho, J.S.;Lim, D.H.;Lee, J.S.;Kim, I.Y.
    • Journal of rehabilitation welfare engineering & assistive technology
    • /
    • v.7 no.2
    • /
    • pp.47-54
    • /
    • 2013
  • In this paper, we present an inertial sensor-based motion capturing system to measure and analyze whole body movements. This system implements a wireless AHRS(attitude heading reference system) we developed using a combination of rate gyroscope, accelerometer and magnetometer sensor signals. Several AHRS modules mounted on segments of the patient's body provide the quaternions representing the patient segments's orientation in space. We performed 3D motion capture using the quaternion data calculated. And a method is also proposed for calculating three-dimensional inter-segment joint angle which is an important bio-mechanical measure for a variety of applications related to rehabilitation. To evaluate the performance of our AHRS module, the Vicon motion capture system, which offers millimeter resolution of 3D spatial displacements and orientations, is used as a reference. The evaluation resulted in a RMSE of 2.56 degree. The results suggest that our system will provide an in-depth insight into the effectiveness, appropriate level of care, and feedback of the rehabilitation process by performing real-time limbs or gait analysis during the post-stroke recovery process.

  • PDF

Development of a Squat Angle Measurement System using an Inertial Sensor (관성 센서기반 스쿼트 각도 측정 융합 시스템 개발)

  • Joo, Hyo-Sung;Woo, Ji-Hwan
    • Journal of the Korea Convergence Society
    • /
    • v.11 no.10
    • /
    • pp.355-361
    • /
    • 2020
  • The squat is an exercise that can effectively improve the muscle strength of the lower body, which can be performed in a variety of places without restrictions on places including homes. However, injuries due to incorrect motion or excessive angles are frequently occurring. In this study, we developed a single sensor-based squat angle measurement system that can inform the squat angle according to the correct motion during the squat exercise. The sensor module, including the acceleration sensor and the gyro sensor, is attached to the user's thigh. The squat angle was calculated using the complementary filter complementing the pros and cons of acceleration and gyro sensor. It was found that the calculated squat angle showed the proper correlation compared to the squat angle measured by a goniometer, and the influence of the coefficient of the complementary filter on the accuracy was evaluated.

Performance Improvement of an AHRS for Motion Capture (모션 캡쳐를 위한 AHRS의 성능 향상)

  • Kim, Min-Kyoung;Kim, Tae Yeon;Lyou, Joon
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.21 no.12
    • /
    • pp.1167-1172
    • /
    • 2015
  • This paper describes the implementation of wearable AHRS for an electromagnetic motion capture system that can trace and analyze human motion on the principal nine axes of inertial sensors. The module provides a three-dimensional (3D) attitude and heading angles combining MEMS gyroscopes, accelerometers, and magnetometers based on the extended Kalman filter, and transmits the motion data to the 3D simulation via Wi-Fi to realize the unrestrained movement in open spaces. In particular, the accelerometer in AHRS is supposed to measure only the acceleration of gravity, but when a sensor moves with an external linear acceleration, the estimated linear acceleration could compensate the accelerometer data in order to improve the precision of measuring gravity direction. In addition, when an AHRS is attached in an arbitrary position of the human body, the compensation of the axis of rotation could improve the accuracy of the motion capture system.

Design of a Compact GPS/MEMS IMU Integrated Navigation Receiver Module for High Dynamic Environment (고기동 환경에 적용 가능한 소형 GPS/MEMS IMU 통합항법 수신모듈 설계)

  • Jeong, Koo-yong;Park, Dae-young;Kim, Seong-min;Lee, Jong-hyuk
    • Journal of Advanced Navigation Technology
    • /
    • v.25 no.1
    • /
    • pp.68-77
    • /
    • 2021
  • In this paper, a GPS/MEMS IMU integrated navigation receiver module capable of operating in a high dynamic environment is designed and fabricated, and the results is confirmed. The designed module is composed of RF receiver unit, inertial measurement unit, signal processing unit, correlator, and navigation S/W. The RF receiver performs the functions of low noise amplification, frequency conversion, filtering, and automatic gain control. The inertial measurement unit collects measurement data from a MEMS class IMU applied with a 3-axis gyroscope, accelerometer, and geomagnetic sensor. In addition, it provides an interface to transmit to the navigation S/W. The signal processing unit and the correlator is implemented with FPGA logic to perform filtering and corrrelation value calculation. Navigation S/W is implemented using the internal CPU of the FPGA. The size of the manufactured module is 95.0×85.0×.12.5mm, the weight is 110g, and the navigation accuracy performance within the specification is confirmed in an environment of 1200m/s and acceleration of 10g.

Development of Wireless Ambulatory Measurement System based on Inertial Sensors for Gait Analysis and its Application for Diagnosis on Elderly People with Diabetes Mellitus (관성센서 기반의 무선보행측정시스템 개발 및 노인 당뇨 환자 보행 진단에의 응용)

  • Jung, Ji-Yong;Yang, Yoon-Seok;Won, Yong-Gwan;Kim, Jung-Ja
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.48 no.2
    • /
    • pp.38-46
    • /
    • 2011
  • 3D motion analysis system which is currently widely used for walking analysis has limitations due to both necessity of wide space for many cameras for measurement, high cost, and complicated preparation procedure, which results in low accessability in use and application for clinical diagnosis. To resolve this problem, we developed 3-dimensional wireless ambulatory measurement system based on inertial sensor which can be easily applicable for clinical diagnosis for lower extremity deformity and developed system was evaluated by applying for 10 elderly people with diabetes mellitus. Developed system was composed of wireless ambulatory measurement module that consists of inertial measurement unit (IMU) which measures the gait characteristics, microcontroller which collects and precesses the inertial data, bluetooth device which transfers the measured data to PC and Window's application for storing and processing and analyzing received data. This system will utilize not only to measure lower extremity (foot) problem conveniently in clinical medicine but also to analyze 3D motion of human in other areas as sports science, rehabilitation.